Token导航 LogoToken导航

Agent Skill · 研究检索

three-dimensional-memory(三度空间记忆)

three-dimensional-memory 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

three-dimensional-memory 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 8,521。

总安装 16,157周安装 660GitHub Stars 公开资料未说明下载 5,227核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:three-dimensional-memory(三度空间记忆)
来源仓库:https://github.com/amlyx/three-dimensional-memory
安装命令:
openclaw skills install three-dimensional-memory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install three-dimensional-memory

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

通过跨三个维度组织文件来管理 AI 助手内存:时间线日志、完整对话备份和基于主题的项目文件夹,以便轻松查看

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install three-dimensional-memory;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

three-dimensional-memory 怎么安装?

在终端执行 openclaw skills install three-dimensional-memory。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

three-dimensional-memory 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

three-dimensional-memory 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

three-dimensional-memory 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

three-dimensional-memory 用的人多吗?

公开数据是累计安装 16,157 次,近一周安装 660 次,下载 5,227 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

three-dimensional-memory 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
three-dimensional-memory

三度空间记忆 · 本页

16,157—需要联网MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

three-dimensional-memory

Three-Dimensional Memory System for AI Assistants — 人类思维方式的文件记忆管理

A memory management system that mirrors human cognition: organized by time, conversation, and topics.


🎯 Why This Skill?

Traditional file management organizes by file type (docs, images, videos). Humans don't think that way.

Humans remember:

  • When it happened (time)
  • What was said (conversation)
  • What it was about (topic)

This skill creates a three-dimensional memory space for AI assistants and their users.


🧠 The Three Dimensions

Dimension 1: Timeline Memory

memory/
├── 2026-02-21.md    ← What happened today
├── 2026-02-22.md    ← What happened today
└── 2026-02-23.md    ← What happened today

Purpose: Daily work logs, chronological record of events Update frequency: Daily Content: Tasks completed, decisions made, meetings held


Dimension 2: Conversation Stream

AI-memory-backup/
├── backup-20260221.md    ← Complete conversation transcript
├── backup-20260222.md    ← Complete conversation transcript
└── backup-20260223.md    ← Complete conversation transcript

Purpose: Full context preservation, searchable dialogue history Update frequency: Per conversation Content: Every word exchanged, including user messages and AI responses


Dimension 3: Topic Network

topic-memory/
├── project-product-launch/
│   ├── proposal-v1.md
│   ├── proposal-v2.md
│   └── final-version.md
│
├── decision-org-restructure/
│   ├── options-considered.md
│   ├── final-decision.md
│   └── implementation-plan.md
│
└── knowledge-market-analysis/
    ├── competitor-research.md
    └── trend-report.md

Purpose: Project-centric information aggregation Update frequency: As projects evolve Content: All documents, decisions, and knowledge related to a specific topic


📁 Recommended File Structure

workspace/
│
├── memory/                      ← Dimension 1: Timeline
│   ├── 2026-02-21.md
│   ├── 2026-02-22.md
│   └── 2026-02-23.md
│
├── AI-memory-backup/            ← Dimension 2: Conversation
│   ├── backup-20260221.md
│   ├── backup-20260222.md
│   └── backup-20260223.md
│
├── topic-memory/                ← Dimension 3: Topics
│   ├── project-[name]/
│   ├── decision-[name]/
│   ├── system-[name]/
│   └── knowledge-[name]/
│
├── skills/                      ← AI capabilities
│
├── MEMORY.md                    ← AI's long-term identity
├── SOUL.md                      ← AI's personality
└── USER.md                      ← User preferences

🚀 Quick Start

Step 1: Initialize Structure

Create the three directories in your workspace:

mkdir -p memory
mkdir -p AI-memory-backup
mkdir -p topic-memory

Step 2: Daily Workflow

Every day, the AI should:

  1. Write to memory/YYYY-MM-DD.md

- Summary of today's work - Decisions made - Tasks completed

  1. Backup conversation to AI-memory-backup/backup-YYYYMMDD.md

- Full transcript - Important context - User preferences learned

  1. Update relevant topic-memory/ folders

- Add new documents to projects - Update decision records - Consolidate knowledge

Step 3: Access Information

Find by time: "What did we do on Monday?" → Check memory/

Find by context: "What exactly did I say about pricing?" → Check AI-memory-backup/

Find by topic: "Where's the product launch plan?" → Check topic-memory/project-product-launch/


📝 Example: A Day in Three Dimensions

Scenario: Product Strategy Meeting

Dimension 1 - memory/2026-02-23.md:

# 2026-02-23 Work Log

## Morning
- Product strategy meeting with CEO
- Decided on three-tier pricing model
- Delayed launch by 2 weeks for additional testing

## Afternoon  
- Drafted pricing proposal
- Created financial projections
- Scheduled follow-up for tomorrow

## Decisions
- ✅ Adopt tiered pricing (Basic/Pro/Enterprise)
- ✅ Delay launch from March 1 → March 15
- ❌ Do not offer early-bird discounts

Dimension 2 - AI-memory-backup/backup-20260223.md:

# Conversation Backup - 2026-02-23

## Product Pricing Discussion

User: "We need to decide on pricing today."

AI: "What are you considering?"

User: "I'm thinking three tiers: $29, $99, $299"

AI: "Have you considered the psychology of pricing? 
      $29 might signal 'cheap', $299 signals 'premium'."

User: "Good point. Let's go with $39, $99, $299"
[Full conversation continues...]

Dimension 3 - topic-memory/project-product-launch/:

# Product Launch Project

## pricing-strategy.md (updated today)
Final decision: Three-tier model
- Starter: $39/month
- Professional: $99/month  
- Enterprise: $299/month

## timeline.md (updated today)
Launch date: March 15, 2026 (delayed from March 1)

## key-decisions.md
- Pricing tiers finalized (2026-02-23)
- Launch delayed for QA (2026-02-23)

💡 Best Practices

For Users

  1. Review daily logs weekly - Quick scan of what happened
  2. Search conversation backups - Find exact quotes and context
  3. Use topic folders - Navigate by project, not by file type
  4. Keep MEMORY.md updated - AI's identity and your preferences

For AI Assistants

  1. Update all three dimensions daily - Don't skip any
  2. Be consistent with naming - Use clear, searchable topic names
  3. Cross-reference - Link between dimensions when relevant
  4. Maintain the index - Keep a master index of active topics

🔍 Troubleshooting

"I can't find a file" → Check all three dimensions. If it's not in timeline or topic, search conversation backup.

"There's duplicate information" → That's by design! Timeline shows when, topic shows what, conversation shows why.

"The AI forgot what we discussed" → Check AI-memory-backup/. The full context is there.


🌟 Why It Works

Traditional file management: "Where did I save that document?"

Three-dimensional memory: "We discussed pricing in yesterday's meeting" → Check memory/2026-02-23.md → Find reference to topic-memory/project-pricing/ → Open latest version

Result: Find files in 10 seconds instead of 5 minutes.


📄 Metadata

  • Author: @openclaw-user
  • Created: 2026-02-23
  • Version: 1.0.0
  • License: MIT
  • Tags: memory, organization, productivity, workflow

*"The best file system is the one you don't have to think about."*

平台分布

OpenClaw

89.57%
按下载量换算4,682

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills